Economic and financial modeling and planning is commonly used to estimate or predict the performance and outcome of real systems, given specific sets of input data of interest. An economic-based system will have many variables and influences which determine its behavior. A model is a mathematical expression or representation which predicts the outcome or behavior of the system under a variety of conditions. In one sense, it is relatively easy, in the past tense, to review historical data, understand its past performance, and state with relative certainty that the system's past behavior was indeed driven by the historical data. A much more difficult task, but one that is extremely valuable, is to generate a mathematical model of the system which predicts how the system will behave, or would have behaved, with different sets of data and assumptions. While forecasting and backcasting using different sets of input data is inherently imprecise, i.e., no model can achieve 100% certainty, the field of probability and statistics has provided many tools which allow such predictions to be made with reasonable certainty and acceptable levels of confidence.
In its basic form, the economic model can be viewed as a predicted or anticipated outcome of a mathematical expression, as driven by a given set of input data and assumptions. The input data is processed through the mathematical expression representing either the expected or current behavior of the real system. The mathematical expression is formulated or derived from principles of probability and statistics, often by analyzing historical data and corresponding known outcomes, to achieve a best fit of the expected behavior of the system to other sets of data, both in terms of forecasting and backcasting. In other words, the model should be able to predict the outcome or response of the system to a specific set of data being considered or proposed, within a level of confidence, or an acceptable level of uncertainty. As a simple test of the quality of the model, if historical data is processed through the model and the outcome of the model, using the historical data, is closely aligned with the known historical outcome, then the model is considered to have a high confidence level over the interval. The model should then do a good job of predicting outcomes of the system to different sets of input data.
Economic modeling has many uses and applications. One emerging area in which modeling has exceptional promise is in the retail sales environment. Grocery stores, general merchandise stores, specialty shops, and other retail outlets face stiff competition for limited customers and business. Most if not all retail stores make every effort to maximize sales, volume, revenue, and profit. Economic modeling can be a very effective tool in helping the store owners and managers achieve these goals.
Retail stores engage in many different strategies to increase sales, volume, revenue, and profit. One common approach is to offer promotions on select merchandise. The store may offer one or more of its products at temporary sale price, discounts for multiple item purchases, or reduced service charges. One or more items may be offered with a percentage off regular price, fixed reduced price, no interest financing, no sales tax, or the well-known “buy two get one free” sale. The store may run advertisements, distribute flyers, and place promotional items on highly visible displays and end-caps (end displays located on each isle). In general, promotional items are classified by product, time of promotion, store, price reduction, and type of promotion or offer.
The process by which retailers select and implement promotional programs varies by season, region, company philosophy, and prior experience. Some retailers follow the seasonal trends and place on promotion those items which are popular or in demand during the season. Summertime is for outdoor activities; Thanksgiving and Christmas are for festive meals, home decorations, and gift giving; back-to-school is new clothes and classroom supplies. Some retailers use flyers and advertisements in newspapers, television, radio, and other mass communication media for select merchandise on promotion, without necessarily putting every item at a reduced price. Some retailers try to call attention to certain products with highly visible displays. Other retailers follow the competition and try to out-do the other. Still other retailers utilize loss-leaders and sell common items at cost or below cost in an effort to get customers into the store to hopefully buy other merchandise. The retailers may also focus on which other items will sell with the promotional items.
Promotional programs are costly and time consuming. Flyers and advertisements are expensive to run, base margins are lost on price reductions, precious floor-space and shelf-space are dedicated to specific items, and significant time and energy are spent setting up and administering the various promotions implemented by the retailer. It is important for the retailer to get good results, i.e. net profit gains, from the promotional investments. Yet, most if not all retailers make promotional decisions based on canned programs, gross historical perception, intuition, decision by committee, and other non-scientific indicators. Many promotional plans are fundamentally based on the notion that if we did it in the past it must be good enough to do again. In most situations, retailers simply do not understand, or have no objective scientific data to justify, what promotional tools are truly providing the best results on a time dependent per product basis.
Customers make their own buying decisions and do not necessarily follow trends. Retailers may have false understanding as to what factors have been primarily driving previous buying decisions and promotional successes. What has been perceived as working in the past may not achieve the same results today, possibly because the basis for belief in the effectiveness of prior promotion programs is flawed. Other unknown or non-obvious factors may be in play driving customer buying decisions which undermine or reveal the weakness in previous promotions. Economic, demographic, social, political, or other unforeseen factors may have changed and thereby altered the basis for customer buying decisions. In spite of costly and elaborate promotions, retailers not infrequently end up with disappointing sales, lower than expected profits, unsold inventory, and lost opportunities based on promotional guesswork. When a promotional program fails to achieve intended objectives, retailers, distributors, manufacturers, and promotional support organizations all lose confidence and business opportunity.
A need exists for an economic model which helps retailers make effective and successful promotional decisions in view of customer responses.